JournalGuide: bringing authors and journals together

Mudrak, Benjamin

doi:10.1087/20150210

Cited by 5 publications

(2 citation statements)

References 9 publications

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“…Notable publishers such as Elsevier and IEEE (Kang et al, 2015;Curry, 2019;Mudrak, 2015;Rollins et al, 2017) have introduced their journal recommender systems, while other organizations offer both free and commercial alternatives (Small, 1973). This paper aims to present a comprehensive comparison of journal recommender systems while providing researchers insights into the effective utilization of journal recommender systems and facilitating informed decisions regarding journal selection.…”

Section: *Scientificmentioning

confidence: 99%

Enhancing research publication choices: A comparative study of journal recommender systems and their effectiveness

Bouaguel,

Benyounes,

Ncir

2024

Int. j. adv. appl. sci.

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In recent years, there has been a rapid increase in the number of research papers being published, leading to what many feel is an overload of information. This makes it difficult for researchers to choose the right journal for their work. To help with this, journal recommender systems have been suggested as useful tools to help researchers find the most appropriate journals for their research. With so many journals, publishers, and recommender systems to choose from, deciding on the best one can be complicated. This decision depends on several factors, including the publisher, the scientific database, and the specific needs and preferences of the user. In this paper, we offer a detailed comparison of popular journal recommender systems, both theoretically and through experiments, to see how effective they are at making recommendations. We focus on how relevant and helpful these recommendations are. We also provide advice for researchers on how to make the most of these recommender systems to aid in their publishing process.

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Section: *Scientificmentioning

confidence: 99%

Enhancing research publication choices: A comparative study of journal recommender systems and their effectiveness

Bouaguel,

Benyounes,

Ncir

2024

Int. j. adv. appl. sci.

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“…JournalGuide is also an online tool available to guide authors to find fitting journals. It includes more than 40,000 article metadata records from PubMed, CrossRef, and from several publishers and aggregators (Mudrak, 2015). IEEE Publication Recommender and Springer Journal Suggester allow comparing articles from their own collections.…”

Section: Existing Journal Recommendation Systemsmentioning

confidence: 99%

Selecting a text similarity measure for a content-based recommender system

Wijewickrema

Petras

Dias³

2019

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Purpose The purpose of this paper is to develop a journal recommender system, which compares the content similarities between a manuscript and the existing journal articles in two subject corpora (covering the social sciences and medicine). The study examines the appropriateness of three text similarity measures and the impact of numerous aspects of corpus documents on system performance. Design/methodology/approach Implemented three similarity measures one at a time on a journal recommender system with two separate journal corpora. Two distinct samples of test abstracts were classified and evaluated based on the normalized discounted cumulative gain. Findings The BM25 similarity measure outperforms both the cosine and unigram language similarity measures overall. The unigram language measure shows the lowest performance. The performance results are significantly different between each pair of similarity measures, while the BM25 and cosine similarity measures are moderately correlated. The cosine similarity achieves better performance for subjects with higher density of technical vocabulary and shorter corpus documents. Moreover, increasing the number of corpus journals in the domain of social sciences achieved better performance for cosine similarity and BM25. Originality/value This is the first work related to comparing the suitability of a number of string-based similarity measures with distinct corpora for journal recommender systems.

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Do LIS experts select more appropriate journals than journal finders? A study about LIS journals?

Vara,

Rahimi,

Danesh

2023

Journal of Librarianship and Information Science

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The primary aim of the present study is to provide a comparative-analytical analysis of the proposed results of the Manuscript Matcher with the responses of Library and Information Science experts to select the most appropriate journal for manuscript submission. This study is a kind of applied research conducted using the survey-analytical method with a comparative approach. Data were collected using a researcher-made questionnaire. The designed questionnaire was sent to 38 Library and Information Science (LIS) experts. Moreover, snowball sampling was employed to select a sample of 38 people. Twelve articles published in 12 WOSCC-indexed LIS journals were randomly selected for the Manuscript Matcher analysis. Abstracts and bibliographic data of the articles were sent to the experts. Moreover, the abstracts and titles of the 12 articles were entered in the manuscript matcher, and the results were analyzed and compared with those obtained from experts' opinions. Frequency distribution, percentage, chi-squared (χ2) test, and SPSS software (version 26) were employed for data analysis. More than 70% of the statistical population were assistant professors, 36.8% of experts had more than 40 published articles, 5% had received more than 300 citations, and 2.6% of LIS experts had an h-index above 20. Compared with 62% congruent responses of experts in the target journal selection, the Manuscript Matcher showed an inferior performance of 53% congruent responses. Furthermore, no significant relationship was found between the number of citations and the experts’ h-indexes with the rate of their congruencies in selecting the target journal. Experts were more successful than Manuscript Matcher in selecting the target journal. However, the Manuscript Matcher included comprehensive coverage of publications that can facilitate the selection of a journal for researchers due to the limited knowledge of all journal finders and the time-consuming distinct search processes.

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JournalGuide: bringing authors and journals together

Abstract: Key points• As a result of the considerable (and growing)

Cited by 5 publications

References 9 publications

Enhancing research publication choices: A comparative study of journal recommender systems and their effectiveness

Enhancing research publication choices: A comparative study of journal recommender systems and their effectiveness

Selecting a text similarity measure for a content-based recommender system

Do LIS experts select more appropriate journals than journal finders? A study about LIS journals?

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